The invention relates to the technical field of driverless cars in a structured road intersection area, in particular to a target vehicle trajectory prediction method based on double-layer lane intention inference, which comprises the following steps: acquiring a short-term prediction trajectory of a target vehicle based on extended Kalman filtering; analyzing the short-term prediction trajectory based on a path similarity scoring model, and obtaining a road prediction value selected when the target vehicle enters the intersection; based on the lateral deviation of the target vehicle, constructing a lane selection intention prediction model based on an interactive multi-model, and obtaining a lane prediction value by the lane selection intention prediction model based on the road prediction value; based on the lane prediction value, generating a prediction track of the target vehicle by adopting a quintic polynomial curve method; according to the invention, high-precision prediction can be carried out on driving tracks of other driving vehicles in an intersection scene.
本发明涉及结构化道路交叉口区域下的无人驾驶汽车技术领域,具体涉及一种基于双层车道意图推断的目标车辆轨迹预测方法,包括如下步骤:基于扩展卡尔曼滤波,获取目标车辆的短期预测轨迹;基于路径相似度评分模型分析所述短期预测轨迹,获取目标车辆进入交叉路口时选择的道路预测值;基于目标车辆的横向偏移,构建基于交互式多模型的车道选择意图预测模型,所述车道选择意图预测模型基于所述道路预测值,获取车道预测值;基于所述车道预测值,采用五次多项式曲线方法生成目标车辆的预测轨迹;本发明能够在交叉路口场景下对其他驾驶车辆的行驶轨迹进行高精度的预测。
Target vehicle trajectory prediction method based on double-layer lane intention inference
一种基于双层车道意图推断的目标车辆轨迹预测方法
2024-12-03
Patent
Electronic Resource
Chinese
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